Differentiable, Learnable, Regionalized Process‐Based Models With Multiphysical Outputs can Approach State‐Of‐The‐Art Hydrologic Prediction Accuracy-Reference-Cited by-同舟云学术

Differentiable, Learnable, Regionalized Process‐Based Models With Multiphysical Outputs can Approach State‐Of‐The‐Art Hydrologic Prediction Accuracy

Author:

Feng Dapeng¹^ORCID,Liu Jiangtao¹^ORCID,Lawson Kathryn¹^ORCID,Shen Chaopeng¹^ORCID

Affiliation:

1. Department of Civil and Environmental Engineering The Pennsylvania State University University Park PA USA

Funder

National Science Foundation

U.S. Department of Energy

Publisher

American Geophysical Union (AGU)

Subject

Water Science and Technology

Link

Reference84 articles.

3. Application of a conceptual hydrologic model in teaching hydrologic processes;Aghakouchak A.;International Journal of Engineering Education,2010

4. Automatic differentiation in machine learning: A survey;Baydin A. G.;Journal of Machine Learning Research,2018

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